Jobs

Duties/Responsibilities:

The main functions of this job lie in the areas of data analysis, algorithm and modeling technique development, and client interactions.

• Data analysis: Perform data clean-up and basic statistical analyses and develop an in-depth understanding of large datasets; modify and use various techniques for filtering, pattern identification, feature extraction, and variable selection.
• Algorithms and modeling techniques: Experiment with different types of algorithms and modeling techniques; develop prototypes of promising methods and conduct performance studies; create commercial-quality implementations of algorithms and techniques for use in analysis and production.
• Client interactions: Prepare model reports for communication with internal and external clients; may participate in pre-sales meetings and calls; and provide post-implementation product support.

Masters or doctorate in a field of science, mathematics, or engineering; demonstrated strong abilities in problem-solving and analytics; excellent communication skills and the ability to work both in teams and alone with limited supervision; ability and willingness to learn new fields of mathematics, statistics, and computer science/software development.

In addition, the successful candidate will have strong background in at least two of the following areas:

• Large dataset analysis: Experience with analysis of large datasets. Strong skills in scripting languages such as Perl; knowledge of data-cleaning techniques and their uses on large datasets. Experience in performing basic statistical analyses leading to the understanding of the structure of the data.

• Financial services industry: Work/research experience in credit/fraud risk management as related to, e.g., mortgage fraud, credit/debit transaction fraud, identity theft, application fraud. Understanding of financial principles and analysis, familiarity with types of risk management issues in the financial services industry.

• Probability/statistics/machine learning: Good working knowledge of several of the following: Bayesian networks, PCA, independent component analysis, linear and logistic regressions, inference, estimation, experimental design, neural networks, SVM.

• Software skill: Strong UNIX background and experience in Perl, C, C++, or Java. Experience with team-based development environment. Familiarity with basic software design principles and coding standards and best practices; ability and interest to acquire further expertise in this area and lead efforts to develop these practice.

• 3+ years of commercial analytical application development experience - strongly desired.